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Add microbenchmark for layer normalization
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108 changes: 108 additions & 0 deletions
108
onnxruntime/test/onnx/microbenchmark/layer_normalization.cc
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| Original file line number | Diff line number | Diff line change |
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| #include "core/platform/threadpool.h" | ||
| #include "core/util/thread_utils.h" | ||
| #include <benchmark/benchmark.h> | ||
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| #if defined(__GNUC__) && !defined(__clang__) | ||
| #pragma GCC diagnostic push | ||
| #pragma GCC diagnostic ignored "-Wmaybe-uninitialized" | ||
| #endif | ||
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| #include "core/framework/allocator.h" | ||
| #include "core/framework/config_options.h" | ||
| #include "core/framework/data_transfer_manager.h" | ||
| #include "core/framework/op_kernel_info.h" | ||
| #include "core/framework/ort_value_name_idx_map.h" | ||
| #include "core/platform/windows/env.h" | ||
| #include "core/providers/cpu/nn/layer_norm_impl.h" | ||
| #include "core/providers/cpu/cpu_provider_factory.h" | ||
| #include "core/providers/cpu/cpu_provider_factory_creator.h" | ||
| #include "core/util/thread_utils.h" | ||
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| #if defined(__GNUC__) && !defined(__clang__) | ||
| #pragma GCC diagnostic pop | ||
| #endif | ||
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| using namespace onnxruntime; | ||
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| template<typename T, typename U> | ||
| static void BM_LayerNormalization(benchmark::State& state) { | ||
| bool simplified = false; | ||
| const float epsilon = 1e-05f; | ||
| int64_t axis = 1; | ||
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| onnxruntime::Node node; | ||
| // Required by LayerNormImpl constructor | ||
| node.AddAttribute("axis", axis); | ||
| node.AddAttribute("epsilon", epsilon); | ||
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| KernelDef kernel_def; | ||
| std::unique_ptr<IExecutionProvider> execution_provider = CPUProviderFactoryCreator::Create(true)->CreateProvider(); | ||
| std::unordered_map<int, OrtValue> constant_initialized_tensors; | ||
| OrtValueNameIdxMap mlvalue_name_idx_map; | ||
| DataTransferManager data_transfer_mgr; | ||
| AllocatorMap allocators; | ||
| ConfigOptions config_options; | ||
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| OpKernelInfo op_kernel_info(node, kernel_def, *execution_provider, constant_initialized_tensors, mlvalue_name_idx_map, | ||
| data_transfer_mgr, allocators, config_options); | ||
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| LayerNormImpl layer_norm_impl(op_kernel_info); | ||
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| std::vector<int64_t> x_dims{2, 2, 2}; | ||
| TensorShape x_shape(x_dims); | ||
| std::vector<float> x{1, 1, 1, 1, 1, 1, 1, 1}; | ||
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| std::vector<int64_t> scale_bias_dims{1, 2, 2}; | ||
| TensorShape scale_shape(scale_bias_dims); | ||
| TensorShape bias_shape(scale_bias_dims); | ||
| std::vector<float> scale{1, 1, 1, 1}; | ||
| std::vector<float> bias{1, 1, 1, 1}; | ||
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| T* X_data = static_cast<T*>(malloc(x.size() * sizeof(T))); | ||
| T* scale_data = static_cast<T*>(malloc(scale.size() * sizeof(T))); | ||
| T* bias_data = static_cast<T*>(malloc(bias.size() * sizeof(T))); | ||
| for (size_t i = 0; i < x.size(); i++) { | ||
| X_data[i] = T(x[i]); | ||
| } | ||
| for (size_t i = 0; i < scale.size(); i++) { | ||
| scale_data[i] = T(scale[i]); | ||
| } | ||
| for (size_t i = 0; i < bias.size(); i++) { | ||
| bias_data[i] = T(bias[i]); | ||
| } | ||
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| T* Y_data = static_cast<T*>(malloc(x.size() * sizeof(T))); | ||
| U* mean_data = static_cast<U*>(malloc(x.size() * sizeof(U))); | ||
| U* inv_std_dev_data = static_cast<U*>(malloc(x.size() * sizeof(U))); | ||
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| OrtThreadPoolParams tp_params; | ||
| tp_params.name = ORT_TSTR("intra-op"); | ||
| std::unique_ptr<concurrency::ThreadPool> thread_pool = concurrency::CreateThreadPool( | ||
| &Env::Default(), tp_params, concurrency::ThreadPoolType::INTRA_OP); | ||
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| for (auto _ : state) { | ||
| auto status = layer_norm_impl.ComputeWithoutContext(X_data, x_shape, scale_data, scale_shape, bias_data, bias_shape, | ||
| Y_data, mean_data, inv_std_dev_data, thread_pool.get(), axis, epsilon, simplified); | ||
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| if (! status.IsOK()) | ||
| { | ||
| std::cout << "ComputeWithoutContext status not OK: " << status.ErrorMessage() << std::endl; | ||
| break; | ||
| } | ||
| } | ||
| } | ||
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| BENCHMARK(BM_LayerNormalization<float, float>) | ||
| ->Arg(1) | ||
| ->Arg(256) | ||
| ->Arg(1024) | ||
| ->UseRealTime() | ||
| ->Unit(benchmark::TimeUnit::kMicrosecond); | ||
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| BENCHMARK(BM_LayerNormalization<MLFloat16, MLFloat16>) | ||
| ->Arg(1) | ||
| ->Arg(256) | ||
| ->Arg(1024) | ||
| ->UseRealTime() | ||
| ->Unit(benchmark::TimeUnit::kMicrosecond); |